Use of Large Language Models in Secondary Education: Student Perspective

Keywords:
Large Language Models, Chatbots, Secondary Education, Artificial Intelligence, Ethics.

Abstract:
This paper presents a revision of the usage of Large Language Models (LLMs) in secondary education and the detailed results of the questionnaire completed by students. The questionnaire was divided into different categories: General Use of LLMs; Copying vs Evaluating LLM Output; Critical Thinking & DecisionMaking; Ethics & Awareness; and Open-Ended Reflection. The study was conducted with 53 students (n=53), aged between 13 and 18 years old. The results related to the General Use of LLMs showed that 92.5% of students use LLMs in their studies, only 1 student did not use any LLMs for academic purposes, and ChatGPT is the most commonly used LLM for academic purposes. From the category in which students use LLMs, we see that the percentage of students who mainly use LLMs for understanding difficult questions is 75.5%. 66% of them use LLMs when they do not understand something. Copying vs. Evaluating LLM Output category showed that students mostly used LLMs to rewrite content in their own words (52.8%). The Critical Thinking & Decision-Making category showed that 67.9% of the students notice when an LLM produces misleading information, and that some investigate further when they have a problem with an LLM’s answer, but their confidence in judging whether an LLM’s answer is correct is neutral (43.4%). Ethics & Awareness showed us that students are not very aware of the institution’s rules about the use of LLM (41.5%).

CITATION:

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M. Vukojičić, I. Korica, “Use of Large Language Models in Secondary Education: Student Perspective,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2026, pp. 60-67. doi:10.15308/Sinteza-2026-60-67

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Vukojičić, M., Korica, I. (2026). Use of Large Language Models in Secondary Education: Student Perspective. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2026-60-67

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